Studies have shown that people who track what they eat on paper, in an app, or in some other record, have better success at losing weight, managing their diet, controlling their portions, and sticking to healthy eating habits. For example, individuals who keep a food diary, or a regular log of what they've eaten and when, are more conscious of what they've eaten and are better able to maintain a healthy diet, even without counting calories. One study concluded that people who kept a journal were more likely to keep the weight they lost off, and another review of studies concluded that people who kept a record of their meals and kept up with diet and exercise lost nearly twice as much weight as people who did not keep a log. (Kaiser Permanente. “Keeping A Food Diary Doubles Diet Weight Loss, Study Suggests.” ScienceDaily, 8 Jul. 2008. www.sciencedaily.com/releases/2008/07/080708080738.htm.)
Tools have been developed to help individuals track their diets. Current trackers enable users to access food data by searching various databases of foods. There are many drawbacks, however, with this approach. The databases are often incomplete and the foods that the user is searching for are not included or the search results do not correlate well to the intended food the user is searching for. For example, searching for peppers brings up different color peppers, different kinds of peppers, e.g., chili versus bell, and different spices.
More importantly, many databases are created with crowd-sourced data so that the data may not be accurate nor is it clear what food information was used to generate each of the food entries. To illustrate this problem, one can do a search using a popular food tracker called MyFitnessPal (MFP) for Chicken Tikka Marsala. The MFP tracker returns approximately 20,000 results all of which are based on different recipes, possibly sides like rice that are served with the dish, and other factors that are not known to the user initiating the search. If the user has ordered a menu item from a restaurant, he may be able to narrow the search by entering the restaurant name as a search term. But even doing that still creates a long list of items that the user needs to search through to try to estimate which item approximates the food that the user is searching for. To illustrate this, consider the following. Potbelly sandwich shops provide a nutrition information page for their sandwiches. A Wreck sandwich is served on multigrain bread, with roast beef, turkey salami, ham and Swiss cheese. Some people choose different kinds of breads, make different meat and cheese choices, and add different toppings (tomatoes, mayo, etc.). A search in MFP for a Potbelly A Wreck sandwich yields 135 different search results ranging from about 220 calories to about 800 calories. There is no way to tell which result, if any, match the combination of ingredients the user is interested in and there is no way from the listing alone that a user could determine if the data is accurate. A user could go to the Potbelly nutrition page and make the custom selections he is interested in and calculate the corresponding nutrition information but then the user would have to manually enter that information into his tracker and save a new Potbelly A Wreck sandwich, making a 136th entry.
Some restaurants also provide only very incomplete information such as the total number of calories for the cheeseburger and fries. There is no way for a user to modify the information if the user only plans to eat half the fries, substitute the fries for a salad, decides to hold the cheese, or adds BBQ sauce to the burger. Other restaurants and venues where people eat, e.g., banquets, company picnics, grab and go counters, pot lucks, dinner parties, etc., don't provide any nutrition information for the foods being served. So a user can only search for the individual ingredients that are easily identifiable in the food served.
Given all of these challenges it is extremely inefficient, time consuming and tedious to ascertain food data and track it. The problems that individuals face in food tracking today are well documented in Barriers and Negative Nudges: Exploring Challenges in Food Journaling, Cordeiro et al. (available at http://www.depstein.net/pubs/fcordeiro_chil5.pdf). The inventive system described below addresses these challenges.